Model Predictive Control Implementation with LabVIEW


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This presentation was presented at National Instruments NIWeek 2007 to demonstrate how to use LabVIEW to implement model predictive control (MPC) strategies to control complicated coax manufacturing processes. Both MatLAB MPC and LabVIEW MPC were implemented in these applications.

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  • Presentation outline What the company product Processes an control system design challenge MPC review System architecture MPC implementation Manufacturing benefit Reference
  • Ultrasound 20 to 200 MHz, fetus check in mother’s womb. C driven, the lower the C, the less energy consumption. Customer: Boston Scientific, Philips, Sonosite, GE Medical, Simens Patient Monitoring: buy cable and terminate here, mainly leakage current for Defibrillation TDI: Tektronix, Agilent, Teradyne. Td driven Surgical: Striker, Karal Storz Imaging (KSI) Surgical: impedance driven, sterilization, autoclave. Endoscope used to human body, it is a light system with a tube and light source Radiology: directing medical imaging technologies to diagnose and sometimes treat diseases. Surgical power tools: robot surgery, remote surgery and minimum invasive surgery Surgical catheter: In medicine , a catheter is a tube that can be inserted into a body cavity, duct or vessel. Catheters thereby allow drainage or injection of fluids or access by surgical instruments Pulse oximetry is a non-invasive method allowing the monitoring of the oxygenation of a patient's blood . In medicine , a Holster monitor (also called an ambulatory electrocardiography device ), named after its inventor, Dr. Norman J. Holster , is a portable device for continuously monitoring the electrical activity of the heart for 24 hours or more Defibrillation is the definitive treatment for the life-threatening cardiac arrhythmias ventricular fibrillation and pulseless ventricular tachycardia Electrophysiology is the study of the electrical properties of biological cells and tissues.
  • PRECISION INTERCONNECT cable solutions enable OEMs to offer clearer and more detailed images in the widest range of applications - from conventional hand-held to the most demanding high density packaging of transesophageal probes, gastroscopes and catheters. These solutions are made possible by: Micro-miniature fine wire handling as small as 56 AWG Ultra low capacitance with air enhanced dielectrics Up to 2000 signal lines in one cable for 2 1/2 and 3D arrays OEMs rely on this expertise in low capacitance, high density packaging, electrical and mechanical consistency and high overall reliability. In addition, PRECISION INTERCONNECT cable assemblies can withstand the mechanical challenges inherent in hand-held devices, i.e. the need for flexibility, flex-life, even the ability to endure repeated disinfection and sterilization. EP: electrophysiology BASIS: basic design for surgical imaging system Blue ribbon for logic analyzer. EMS: emergency medical service Product consistency unparalleled in the industry is made possible by innovative equipment such as state-of-the-art closed-loop-control systems.
  • Each layer is one process with related automated equipment.
  • Skew is the biggest difference among all coax time delays. Product quality Outputs: C, D, Td, Z0, skew Inline measurement: C, D, d, to calculate Z0, Td Ultrasound coax: C quality TDI: Td quality, Z0 Patient Monitoring: Surgical:
  • Extrusion Process: Taping Process: Line speed and distance between actuators and sensors change Constraints: for instance: tape tension range, Capacitance range IO setpoints: Cap target, more inputs to provide input targets Disturbance: tape spool edge thickness variation.
  • Control moves from k to m-1, m is control horizon. Output setpoint tracking: force the plant outputs to follow their setpoints Input setpoint tracking: force the plant inputs to follow their setpoints for plants with more inputs than outputs, the inputs are not unique unless defining some inputs as their setpoints to follow. The setpoints usually represent operating conditions that improve safety, economic return, etc. Control move suppression: the controller’s setpoint tracking degrade; less sensitive to prediction inaccuracies (more robust)
  • Control horizon nc: Predictive horizon: Why the controller bothers to optimize over P future sampling periods and calculate M future moves when it discards all but the first move in each cycle? Constraints: given sufficiently long horizons, the controller can “see” a potential constraint and avoid it or at least minimize its adverse effects. Plant delays: suppose that the plant includes a pure time delay equivalent to D sampling instants. In other words, the controller’s current move, uk, has no effect until yk_D_1. In this situation it is essential that P>>D and M<<P-D, as this forces the controller to consider the full effect of each move. Non-minimum phase plants: consider a SISO plant with an inverse-response, i.e., a plant with a short-term response in one direction, but a longer term response in the opposite direction. The optimization should focus primarily on the longer term behavior. Otherwise, the controller would move in the wrong direction. Rules of thumb: Choose the control interval such that the plant’s open-loop setting time is about 20 to 30 sampling periods (i.e., the sampling period is approximately one fifth of the dominant time constant). Choose prediction horizon P to be the number of sampling periods used in step 1. Use a relative small control horizon M e.g., 3-5
  • Local control: PAC such as NI compact field point and compactRIO, or PLC OPC server: OLE for Process Control using Microsoft COM, interface between local controls with the central control with OPC Client software PC-Ethernet-based control system with LabVIEW to do HMI and overall MPC control for product quality control and data logging. MIS: OPC and database technologies to log real-time data. 1. For instance: Citadel database in DSC module, 2.MS SQL database using database toolkit. 3. Industrial SQL server from Wonderware Report program: NI report generation, Crystal Report, MS report software, WW Activefactory. Reports are productivity reports, product quality reports, machine utilization reports, real-time trending and statistics reports.
  • Organize the hardware and software in one place PC software: 1. Labview lib, support files, dependency, and shared variable engine as OPC Server, build application and installer configuration 2. Hardware: cFP2020 configuration, software runs on hard real-time processor with auto startup feature; build application and deploy it as auto startup.
  • RT allows to hard real-time code running in cFP hardware DSC to configure the scaling, alarm, and data logging, and shared variable engine as OPC server Simulate the process, and control design for MPC controller. Advance signal processing for filter design and real-time FFT analysis. Database for recipe upload Internet for recipe display on the internet to print out. Report generation for product quality real-time report for spool quality label
  • MPC design with input and output constraints, time delay and models MPC implementation Control action outputs
  • Define np and nu Define input and output setpoint profile Give to MPC implementation VI
  • Taping application Manual mode to show the disturbance and normal operating condition Auto mode to set setpoint following and disturbance rejection. Output weight on impedance, let OD free. Histogram and real-time trending charts Z and FOD Output constraints. Alarm to stop machine and quality tracking
  • Use Matlab m script server with LabVIEW Same way to design MPC
  • MPC m script node with code in it
  • MPC implementation Manual to show the disturbance and operating condition Auto to show setpoint following and disturbance rejection Weighting factor the same. Point out the issues on this approach - Matlab software required - simulate in Matlab and in Labview, and then implement in Labview - software upgrades to make sure the interface works between Matlab and Labview - Tech support not as good
  • Extrusion process graph explanation Time delay mode but control OD automatically. Point to the label printing and spool quality checking, alarm tracking, etc Screw speed and line speed feedforward compensation to increase productivity
  • Output weighting Original OD weighting higher, and then Z weighting higher to see the setpoint following effects based on the weight tuning parameters. Feedforward compensation, spool summary, and quality label for test reduction
  • Company product win third party test result for consistent quality. Taping line setup eliminate night shift Feedforward line speed/screw speed ramp up Laser gauge elimination due to multivariable MPC controller. For instance, dielectric OD laser malfunction, operator did not see it, but the controller acted up, therefore detect sensor fault On-line quality tracking and prediction, reduced off-line coax test.
  • Model Predictive Control Implementation with LabVIEW

    1. 2. Model Predictive Control Implementation with LabVIEW Yurong Kimberly Wang, Ph.D. Principal Control Systems Engineer Tyco Electronics Wilsonville, Oregon
    2. 3. Tyco Electronics / Precision Interconnect
    4. 5. Coax Manufacturing Processes <ul><li>Dielectric layer </li></ul><ul><ul><ul><li>Taping or Extrusion </li></ul></ul></ul><ul><li>Shield layer </li></ul><ul><ul><ul><li>Braiding or Serving </li></ul></ul></ul><ul><li>Jacket layer </li></ul><ul><ul><ul><li>Taping or Extrusion </li></ul></ul></ul>
    5. 6. Taped or Extruded Coax
    6. 7. Coax Property <ul><li>C: capacitance (pF/Foot) </li></ul><ul><li>Td: time delay (ns/Foot) </li></ul><ul><li>Z 0 : impedance (Ohm) </li></ul><ul><li>k: dielectric constant </li></ul><ul><li>D: outer diameter (Mil) </li></ul><ul><li>d: center conductor diameter (Mil) </li></ul><ul><li>Formulae </li></ul>
    7. 8. Process Control Challenge <ul><li>Multiple Outputs </li></ul><ul><ul><ul><li>Capacitance, Diameter, Time delay, Impedance, … </li></ul></ul></ul><ul><li>Multiple Inputs </li></ul><ul><ul><ul><li>Screw speed, line speed, barrel temperatures, tape tensions, … </li></ul></ul></ul><ul><li>Long and Variable Time Delays </li></ul><ul><ul><ul><li>Variable line speeds and sensor to actuator distances </li></ul></ul></ul><ul><li>Input and Output Constraints </li></ul><ul><ul><ul><li>Input and output upper and lower spec limits </li></ul></ul></ul><ul><li>Nonlinearity </li></ul><ul><ul><ul><li>Variety of operating conditions </li></ul></ul></ul><ul><li>Disturbances </li></ul><ul><ul><ul><li>Center conductor variation, tape thickness variation, … </li></ul></ul></ul>
    8. 9. Model Predictive Control (MPC) Law <ul><li>Model-based multi-variable control </li></ul><ul><li>Optimal control law with I/O constraints </li></ul><ul><li>Nonlinear control with model mismatch </li></ul><ul><li>Long and variable time delay process </li></ul>
    9. 10. MPC System and Optimization
    10. 11. MPC Sampling Instants
    11. 12. System Architecture Production Quality Engineers Production Plant Managers Production Process Engineers Production Manufacturing Engineers Manufacturing Information Server Business Network Report Program for Data Analysis Production Remote Users Internet Control Network Local Control Module Local Control Module Local Control Module Business Network OPC Client & Server for Data Logging OPC Client & Server for Data Sharing Production LabVIEW HMI & MPC Control Figure 1. System Architecture Local Control Module
    12. 13. LabVIEW Project Explorer
    13. 14. LabVIEW – Based Application <ul><li>LabVIEW Professional Development </li></ul><ul><li>LabVIEW Real-Time Module </li></ul><ul><li>Data Logging and Supervisory Control Module </li></ul><ul><li>Simulation Module </li></ul><ul><li>Control Design Toolkit </li></ul><ul><li>Advanced Signal Processing Toolkit </li></ul><ul><li>Database Connectivity Toolkit </li></ul><ul><li>Internet Connectivity Toolkit </li></ul><ul><li>Report Generation Toolkit </li></ul><ul><li>Compact FieldPoint Hardware and Device Drivers </li></ul>
    14. 15. LabVIEW MPC Implementation
    15. 16. LabVIEW MPC Code
    16. 17. LabVIEW MPC Application Manual to auto control with disturbance rejection
    17. 18. MatLAB TM MPC – Initial Approach
    18. 19. MatLAB MPC Script Node
    19. 20. MatLAB MPC Application Manual to auto control with disturbance rejection
    20. 21. Polymer Extrusion MPC HMI
    21. 22. MPC Output Weighting Effect
    22. 23. Manufacturing Benefit <ul><li>Consistent product quality </li></ul><ul><ul><li>Multi-variable auto-controlled product quality </li></ul></ul><ul><li>Productivity improvement </li></ul><ul><ul><li>Unmanned overnight MPC control with alarm monitoring </li></ul></ul><ul><ul><li>Production speed auto ramp with feedforward compensation </li></ul></ul><ul><li>Equipment cost reduction </li></ul><ul><ul><li>Inner tape layer diameter gauge elimination </li></ul></ul><ul><li>Sensor fault detection </li></ul><ul><ul><li>Controller acting up with sensor fault readings </li></ul></ul><ul><li>Labor cost reduction </li></ul><ul><ul><li>Coax quality on-line prediction and off-line test reduction </li></ul></ul>
    23. 24. Reference Material <ul><li>LabVIEW Model Predictive Control Module User Manual </li></ul><ul><ul><li>by National Instruments </li></ul></ul><ul><li>MatLAB Model Predictive Control Toolbox User Manual </li></ul><ul><ul><li>by MathWorks </li></ul></ul><ul><li>Advanced Control Unleashed </li></ul><ul><ul><li>by Terrence L. Blevins, Gregory K. McMillan, Willy K. Wojsznis, and Michael W. Brown, ISA </li></ul></ul><ul><li>Models Unleashed – Virtual Plant and Model Predictive Control Applications, A Pocket Guide </li></ul><ul><ul><li>by Gregory K. McMillan, Robert A. Cameron, ISA </li></ul></ul><ul><li>Dual-Target Predictive Control for Food Extrusion </li></ul><ul><ul><li>by Y. Wang and J. Tan, Control Engineering Practice 8 (2000) </li></ul></ul>